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author:

Yu, QZ (Yu, QZ.) [1] | Chen, CC (Chen, CC.) [2] (Scholars:陈崇成) | Pan, ZG (Pan, ZG.) [3]

Indexed by:

CPCI-S SCIE

Abstract:

Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. This paper describes how fine-grained parallel genetic algorithms can be mapped to programmable graphics hardware found in commodity PC. Our approach stores chromosomes and their fitness values in texture memory on graphics card. Both fitness evaluation and genetic operations are implemented entirely with fragment programs executed on graphics processing unit in parallel. We demonstrate the effectiveness of our approach by comparing it with compatible software implementation. The presented approach allows us benefit from the advantages of parallel genetic algorithms on low-cost platform.

Keyword:

Community:

  • [ 1 ] Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Peoples R China
  • [ 2 ] Fuzhou Univ, Spatial Informat Res Ctr Fujian Province, Fujian 350002, Peoples R China

Reprint 's Address:

  • [Yu, QZ]Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Peoples R China

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Source :

ADVANCES IN NATURAL COMPUTATION, PT 3, PROCEEDINGS

ISSN: 0302-9743

Year: 2005

Volume: 3612

Page: 1051-1059

0 . 4 0 2

JCR@2005

0 . 4 0 2

JCR@2005

JCR Journal Grade:4

Cited Count:

WoS CC Cited Count: 47

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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